Mass spectrometric imaging is a technique for examining the distribution of a substance having specific mass by performing a mass analysis on each of a plurality of small measurement areas (micro-areas) within a two-dimensional region on a sample, such as a piece of biological tissue. This technique is increasingly applied to, for example, discovery and development of new medicines, discovery of biomarkers, and investigation on the causes of various diseases. Mass spectrometers designed for mass spectrometric imaging are generally referred to as imaging mass spectrometers. This type of device may also be referred to as a microscopic mass spectrometer or a mass microscope since it performs a microscopic observation on an arbitrary two-dimensional region on a sample, selects an area to be analyzed based on the resultant microscopic observation image, and performs an imaging mass analysis on the selected area. The term “imaging mass spectrometer” will be used in this specification. For example, Non-Patent Literatures 1 and 2 disclose configurations of general imaging mass spectrometers and their analysis examples.
In an imaging mass spectrometer, mass spectrum data in a predetermined mass-to-charge ratio range is obtained for each of a large number of measurement points within a two-dimensional region on a sample. In order to do that at a high mass resolving power, normally, a time-of-flight mass spectrometer (TOFMS) is used as the mass spectrometer. In this case, the amount of mass spectrum data (or time-of-flight spectrum data) per measurement point is significantly larger than the amount of mass spectrum data in other mass spectrometers such as quadrupole mass spectrometers. Further, in order to obtain a fine mass analysis result image (that is, with an enhanced spatial resolving power), it is necessary to make the interval between the measurement points smaller, so that the number of measurement points on one sample becomes larger. Hence, if mass spectrometric imaging is performed at a high mass resolving power and a high spatial resolving power, the total amount of data per sample is enormous.
In order to create a mass analysis result image, display it, and statistically analyze the mass analysis result image through data processing using a general personal computer, it is necessary to read entire data to be processed into a main memory (generally, a RAM) of the computer. However, there is a restriction on the capacity of the main memory that is actually available in the general personal computer, and hence it is difficult to entirely read such high-resolution imaging mass analysis data as described above into the main memory. In this case, it is necessary to limit the range of images that can be created and displayed for mass analysis result in accordance with the restriction on the amount of data readable into the main memory, or, otherwise, use a part of an external memory device such as a hard disk drive as a virtual main memory, in which case the processing speed inevitably deteriorates.
Against these problems, Patent Literatures 1 to 3 each disclose a technique for storing mass spectrum data obtained by an imaging mass spectrometer after compressing it. The use of such a data compression technique makes it possible to reduce the size of imaging mass analysis data to be processed when reading it into a main memory. Further, according to the technique disclosed in Patent Literature 1, an index for associating the positions of the original (uncompressed) mass spectrum data in an array with the positions of the compressed data in the array is created, and the index is stored together with the compressed data or separately of the compressed data. Then, in the case where data (ion intensity value) corresponding to a given mass-to-charge ratio needs to be read, compressed data corresponding to the desired data is found with reference to such index information, and the data found is decompressed. In this way, desired data can be rapidly obtained even if data compression is used.
The ionization method of a MALDI ion source which is normally used for imaging mass spectrometers is suitable for biological samples, but it has a disadvantage in that the ion intensity fluctuates relatively large for each measurement (that is, for each laser irradiation). In order to compensate for such a disadvantage, when a mass spectrum is to be obtained for one measurement point, measurements are performed many times on the measurement point and the ion intensity signals thus obtained are summed. However, such summing is not always effective for eliminating fluctuations in ion intensity for each measurement point. Hence, even if a mass analysis result image is created using the ion intensity values at a specific mass-to-charge ratio obtained for each measurement point, the created mass analysis result image may not show the true distribution of a substance. In view of this, it is conventionally proposed to use ion intensity values that are normalized based on a predetermined reference instead of using raw ion intensity values at each measurement point, when a mass analysis result image is created.
For example, Non-Patent Literature 1 shows that it is adequate to perform TIC normalization or XIC normalization on imaging mass analysis data and then create, display, and statistically analyze a mass analysis result image. Here, TIC stands for “total ion current”, and means the sum of the ion intensity values within the entire mass-to-charge ratio range on a mass spectrum obtained at each measurement point. With the TIC normalization, the intensity value at each mass-to-charge ratio is normalized so that the TIC at each measurement point is the same. Meanwhile, XIC stands for “extract ion current”, and means the sum of the ion intensity values in a designated mass-to-charge ratio or within a mass-to-charge ratio range on a mass spectrum obtained at each measurement point. With the XIC normalization, the intensity value in each mass-to-charge ratio is normalized such that the XIC at each measurement point is the same, and hence the height of a peak corresponding to a specific mass-to-charge ratio can be equalized at each measurement point.
Further, in order to enable an operator (user) to decide a mass-to-charge ratio or mass-to-charge ratio range for displaying a mass analysis result image, the operator refers in many cases to an average mass spectrum of all measurement points or measurement points within a region of interest on which the operator focuses attention. Creation based on TIC-normalized or XIC-normalized ion intensity values is effective also for such an average mass spectrum.
In mass spectrometric imaging, a common practice is to perform an analysis in which a plurality of imaging mass analysis data respectively obtained from different samples are compared with each other. For example, for a diagnosis of a disease such as a cancer, it is effective to: compare imaging mass analysis data obtained from a piece of biological tissue collected from a healthy body with imaging mass analysis data obtained from a piece of biological tissue collected from a subject; evaluate similarities and differences between them; and analyze different portions in detail. A method used for an objective analysis for such comparison is a statistical analysis such as the principal component analysis on imaging mass analysis data obtained from different samples.
For example, Non-Patent Literature 1 discloses an effective method of comparing plural samples with each other. In the method, peak matrix data is generated for each of imaging mass analysis data of different samples, the plurality of peak matrix data are combined and a statistical analysis is performed on the combined data. Specifically, first, the mass-to-charge ratios of a plurality of peaks to be statistically analyzed are determined in advance for a plurality of imaging mass analysis data to be compared. For example, the mass-to-charge ratios of a plurality of specific peaks are selected from: an average mass spectrum obtained by averaging the mass spectra at all the measurement points of the imaging mass analysis data to be compared; or a maximum intensity mass spectrum obtained by obtaining the maximum intensity in each mass-to-charge ratio of the mass spectrum over all the measurement points and reconstructing the obtained maximum intensity values as a spectrum. Then, from the mass spectrum that is obtained at each measurement point for each sample, the ion intensity value corresponding to the selected mass-to-charge ratio value is obtained, and a peak matrix in which the mass-to-charge ratio value and the ion intensity value are paired is created for each measurement point. After that, the peak matrix data for the plurality of measurement points on the plurality of samples are combined and created into one peak matrix data.
Further, in the statistical analysis disclosed in Non-Patent Literature 1, when peak matrix data of different samples are combined, the intensity values are normalized based on the above-mentioned TIC. As described above, the TIC normalization can reduce influences of fluctuations in an ion intensity value for each sample and influences of fluctuations in amount of ions that are generated for each measurement point by a MALDI ion source, which result from differences in samples, preprocessing, measurement dates, measurement conditions, and other factors. As a result, an effective statistical analysis can be performed.
As described above, in order to combine peak matrices created from the imaging mass analysis data of different samples, it is necessary to calculate an average mass spectrum or a maximum intensity mass spectrum of all measurement points or a plurality of specific measurement points for the imaging mass analysis data to be compared, and then determine in advance the mass-to-charge ratios of a plurality of peaks to be statistically analyzed. This processing is based on the presumption that all the mass-to-charge ratio values of a plurality of mass spectrum data included in the imaging mass analysis data to be compared are the same, in other words, the respective mass-to-charge ratio values at a large number of data points constituting each mass spectrum are common among all mass spectra.
In actual, however, mass spectrometric imaging on a plurality of samples to be compared is not necessarily performed under the same measurement conditions, and imaging mass analysis data obtained by different devices may be compared with each other in some cases. For example, in the case of a mass spectrum obtained by a time-of-flight mass spectrometer, the ion signal intensity is obtained from a detector at regular time intervals from the arrival time at which an ion at the lower limit of a mass-to-charge ratio range to be measured arrives at the detector, and each obtained time is replaced with its corresponding mass-to-charge ratio value to be configured as mass spectrum data. Even if the same device is used, the mass-to-charge ratio value corresponding to the ion time-of-flight needs to be changed appropriately in order to compensate for a change in ion flight distance due to the ambient temperature or other environmental factors. Under such circumstances, the mass-to-charge ratio values at the data points of the plurality of imaging mass analysis data to be compared are not the same in many cases. Further, the measurement point intervals on each sample (in other words, the effective sizes of micro measurement areas for one mass spectrum data) at the time of the mass spectrometric imaging may be different for each sample.
As described above, in the case where the mass-to-charge ratio values at the data points constituting a mass spectrum are different for each sample or where the sizes of the micro measurement areas for a mass spectrum are different for each sample, the peak matrices respectively obtained from the imaging mass analysis data of the plurality of samples cannot be combined according to the above-mentioned conventional method. Hence, in the case where the plurality of samples are to be compared with each other using the statistical analysis, for example, it is necessary to perform the statistical analysis on the peak matrices respectively obtained from the imaging mass analysis data of the samples, adjust the plurality of statistical analysis results thus obtained to be comparable with each other, and then compare the statistical analysis results with each other. Such work is much complicated, and may lower the accuracy of comparison evaluation.
Further, in the case where the plurality of samples are compared with each other as described above, it is also important that: mass analysis result images in specific mass-to-charge ratios or within mass-to-charge ratio ranges on which an operator (user) focuses attention be simultaneously displayed; and the operator subjectively evaluate similarities and the like between them while visually checking the displayed mass analysis result images. However, in the case where the mass-to-charge ratio values at the data points constituting a mass spectrum are different for each sample or where the sizes of the micro measurement areas for a mass spectrum are different for each sample, even if the two-dimensional distribution of a target substance is the same among the plurality of samples, how it looks may be different among them. As a result, the operator may make erroneous subjective determination and evaluation.
Still further, the mass-to-charge ratio values at the data points constituting a mass spectrum are normally equal for each measurement point in imaging mass analysis data for one sample. However, in the case where a change in ion flight distance due to a change in temperature and other factors is corrected as appropriate during the measurement in the time-of-flight mass spectrometer, or depending on how to set measurement conditions, the mass-to-charge ratio values at the data points constituting a mass spectrum may be different for each measurement point. For example, in a measurement method conceivable to reduce the measurement time, only a region of interest that is designated by the operator within the measurement region on one sample is measured at a high mass resolving power, and the other region than the region of interest is measured at a low mass resolving power. It is difficult to create peak matrices for a statistical analysis from the imaging mass analysis data collected under such a condition, regardless of whether or not to combine the peak matrices respectively generated from the plurality of imaging mass analysis data as described above.